An AI video editor is software that uses AI models to help analyse, arrange or change video and audio. It can turn speech into a transcript, find a passage, remove pauses, reframe a shot, generate new visual material or carry out a sequence of edits from your instructions. The available actions depend on the editor and its connected tools.
For example, “remove this repeated sentence” can become a cut in the timeline. “Change the background to a studio” can generate new pixels inside the shot. “Build a short feature announcement from these recordings” can involve choosing clips, adding titles and mixing sound. All three are called AI video editing, but they involve different work.
The useful question is what the AI changes and what you can still revise afterward. This guide explains the process using a finished website-demo template whose screens, text, animation and sound remain available for editing.
What makes a video editor an AI video editor?
An ordinary editing operation follows a precise instruction: trim this clip at this time, set this volume or move this title. AI adds an interpretation step. A model can recognise spoken words, identify a subject, interpret a request or propose how to arrange material before the editing software carries out the change.
That does not require every feature in an editor to use AI. Adobe Premiere, for example, combines a conventional timeline with Text-Based Editing. Its transcript contains timecodes linked to the footage, so selecting and rearranging dialogue can trim and move the corresponding clips. The editor still gives you a timeline for refining those cuts.
Some applications make the transcript the main way you edit. Others put a conversational agent beside the stage. A generative footage editor may concentrate on changing the appearance or contents of a shot. These approaches overlap: one application can offer transcript editing, generated media and an AI assistant together.
| Editing approach | What you ask it to do | What happens underneath |
|---|---|---|
| AI-assisted timeline editing | Find a spoken passage or remove selected filler words | Speech analysis identifies time ranges; the editor applies cuts to the sequence |
| Transcript-led editing | Delete a sentence or rearrange an explanation | Text selections map to the associated audio and video |
| Generative footage editing | Change the setting, lighting or an object | A generative model produces modified visual content |
| Agent-directed project editing | Assemble or revise a complete sequence | An agent plans actions, uses editing tools or changes project files, then examines the result |
For a current example of the second approach, Descript supports editing through a transcript and has Underlord, an AI co-editor that can help with cuts, design, captions and other changes. Transcript-first does not mean it can only remove words.
Runway’s AI video editor illustrates generative footage editing: a user supplies footage, describes a change and previews a reference frame before generating the modified sequence. That can supply a shot for a larger project, rather than replacing the rest of the editing process.
How does an AI video editor work?
The details vary by product, but it helps to separate five stages: inputs, analysis, decisions, editing and output. A tool that only generates captions may use a small part of this process. An agent building a whole video may repeat the stages several times.
1. It receives the media and the task
The inputs can include recordings, images, an existing project, a script and a written request. The software also needs basic production choices such as the intended length, frame shape and audience.
“Make this better” leaves the important decisions open. “Cut this interview to the explanation of the pricing change, preserve the speaker’s qualification and keep it under 45 seconds” identifies both the selection and its constraints.
Source material matters as much as the prompt. A low-resolution recording cannot reveal a small label that was never legible. A generated illustration can support an explanation, but it cannot establish what a real product’s interface looks like.
2. Models make the material searchable or understandable
Speech recognition can produce a transcript linked to times in the recording. Visual analysis can help locate a subject, find relevant footage or guide a crop. Other models can separate a foreground subject, improve speech or identify material that matches a request.
The editor uses the analyses relevant to the feature you requested. It does not necessarily run every model on every upload, and a transcript is not proof that a system understands the whole argument.
For a dialogue cut, the link between words and time is especially useful. If a selected sentence runs from 12 to 17 seconds, the editor has a candidate range to remove or rearrange. The cut still needs a listen: the boundary can include a breath, part of the next word or context the speaker needs.
3. It turns the request into editing decisions
A requested action might be narrowly defined, such as removing a detected silence. A conversational agent can take a broader brief and break it into tasks: select a passage, shorten it, add a title, insert an image and lower the music under the voice.
The agent needs access to tools that can perform those tasks. A chat response suggesting a cut has not changed the video. In an agent-directed studio, the useful result is an updated sequence or project you can preview.
CoAnimator’s creation process uses a connected agent to build scenes while the composition appears on the stage. Its footage-editing tools also support imported recordings, captions, effects and overlays. Which actions the agent can perform depends on its permissions and configured tools.
4. Editing tools apply the changes
Different requests change different parts of a project. Moving a clip changes the sequence. Rewording a title changes a text element. Turning down music changes an audio setting. Replacing a filmed background may require generating new imagery.
Generative editing also exists inside conventional editors. Adobe’s Generative Extend creates additional picture or ambient audio at a clip’s boundary. It uses a cloud model and cannot create or extend spoken dialogue. Extending a reaction shot and inventing a new spoken sentence are separate capabilities.
The saved representation determines what a later correction involves. If the title remains live text, you can change its wording as text. If the words are part of a generated image or a flattened movie, replacing them may require another image, a mask or a new render of the source project.
5. You preview, revise and export
The preview lets you review the sequence before producing the delivery file. It shows whether a sentence is complete, the image matches the idea and the title stays readable long enough.
Rendering draws the frames, combines the picture with the sound and encodes the output. The render itself does not have to involve an AI model: an AI-authored animation can be rendered from its prepared files. CoAnimator, for example, exports project video as an MP4.
Watch that MP4 too. A successful export does not establish that the content is accurate or the edit feels right. Keep the project and assets with it so the next correction has a source to return to.
See how an editable website demo is built
The CoAnimator Website Demo template is a finished 33-second product film. It opens with a typed brief and orbiting agent marks, then reveals a 3D monitor showing scrolling website captures. Music and small sound cues accompany the type, reveals and ending.
Open the template and download its editable .coa project · Watch the Website Demo MP4 directly.
The project is the useful part of the example. Its 1920 × 1080, 60fps timeline keeps the visual animation, website images and sound available as source material. An agent can work on those parts instead of treating the exported movie as the only thing it has to edit.
| Part of the Website Demo | What the source project keeps | A concrete revision |
|---|---|---|
| Opening brief | Text and its animation instructions | Replace the example request with an approved line about your product |
| Website content | Separate image files for the captured websites | Substitute your own current captures |
| Monitor and camera | A 3D model and animation code | Turn the display toward the viewer or hold a detail longer |
| Music | One music clip on its own track | Adjust the level or replace the track |
| Sound accents | Two effects tracks containing 32 timed clips | Move a typing cue or transition sound to match the revised animation |
For example, ask the agent to replace the website capture and change the opening headline while preserving the monitor’s camera movement. That request involves finding the right assets, updating the text and fitting both into the existing composition. If the new headline is longer, its line break and reading time also need attention.
Download the template, then double-click its .coa file or choose Open .coa in CoAnimator. Add your own screenshots and brand assets before requesting a version for your business. Replace example names, URLs and marks that do not belong in your film. Keep the project alongside the exported movie so a later correction can use the original parts.
Another example: editing recorded footage
An AI editor can also work with existing camera footage. This 29.3-second CoAnimator podcast edit keeps the real speakers and dialogue, then adds selective typography, image inserts, music and sound cues. It was created with Claude Code.
Watch the recorded-footage MP4 directly.
The speech, music and effects remain separate in its project, so a music-level change does not require replacing the voice. This illustrates another editing task alongside the website demo above.
Footage: Aaron Lebsack / NIWC Pacific, Next Level Podcast, Episode 7, hosted by Anu Venkatesh with Peter Singer. DVIDS identifies the footage as public domain. The appearance of U.S. Department of War (DoW) visual information does not imply or constitute DoW endorsement.
Music: “Signal to Noise” by Scott Buckley, No Piano Melody mix, under CC BY 4.0. Retain the relevant credits when reusing the clip.
AI video editor, video generator and renderer: what is the difference?
An AI video generator creates visual material. An AI video editor helps change or organise a production. A renderer turns a prepared sequence or composition into output frames and a delivery file. One application can perform all three roles.
| Role | A concrete example | What you should inspect |
|---|---|---|
| Generator | Create an animated background for an explainer | What was generated, its visual consistency and whether details are accurate |
| Editor | Place that shot between two speaker passages and add a title | The sequence, wording, timing and available revision controls |
| Renderer | Produce the final MP4 from the project | Playback, sound, dimensions, duration and the final frame |
An editor can call a generator when a scene needs new material. A generator can accept an existing clip and transform it, which is itself a form of editing. The distinction is the operation being performed, rather than whether the product has “editor” or “generator” in its name.
This is especially useful for product videos. Generate an expressive background if it serves the brief, but use the real screen when a button label or action needs to be exact. Our guide to agentic and generative video explains how agents and generation models fit into the larger production.
What can AI help with, and what still needs a decision?
AI is useful when a task can be expressed clearly and the editor has the right material: locating dialogue, making an initial cut, cleaning speech, adding captions, reframing or carrying out a specified visual change. It can also help a small team build animation that would otherwise require writing or adjusting each scene manually.
The difficult errors often concern meaning and judgement. A clip can be fluent, attractive and wrong about what the speaker said or the product does. Review the specific relationships that could break:
| Request | A plausible failure | What to review |
|---|---|---|
| Remove filler and pauses | A qualification or natural breath disappears | Listen across each join and compare the meaning with the original |
| Add captions | A name, number or technical term is mistranscribed | Read the text against the audio and approved terminology |
| Make a portrait version | The crop follows a face but hides the screen being discussed | Watch the full frame at the destination size |
| Change part of a shot | Unrequested details or motion also change | Compare the subject, background and action across the sequence |
| Update a product demonstration | Old text remains in a title, voice line or callout | Match the screen and every explanation of it to the current product |
Clear instructions reduce ambiguity. They do not eliminate the need to review. “Keep the original voice and remove only the repeated clause” is a more useful direction than asking for a generally tighter edit.
The same applies to quality claims. Fewer clicks can make a task easier, but the number of prompts alone does not measure the finished result. Watch whether a viewer can follow the action, read the text and hear the important sentence.
How to try an AI video editor for the first time
Choose one short passage or one product action. Supply the original media, state what the viewer should understand and ask for a limited change. You will learn more about the editor from a specific request than from asking it to make an entire campaign before you have seen how it handles your source material.
Here is a first-edit brief you can adapt for an opened template or a small existing project:
Copy a first-edit brief
Work in a copy of the project I supplied. Make a 20–30-second explanation of one complete idea, using my approved copy and media. Propose the scenes and the changes you intend to make before building the sequence.
Keep product information from the supplied screens intact. Add only the titles or supplied images that help explain the idea. Keep important controls readable and leave enough time to understand the result. If I supply recorded speech, preserve the speaker’s meaning, qualifications and original voice. Do not invent a product action, statistic or spoken line.
Keep speech, music, titles and source media available for revision where the editor supports it. Use only the supplied media; identify a missing asset rather than requesting paid generation. Let me review the sequence before export, then provide the movie and the project or handoff files the application supports.
After the first version, ask for one ordinary correction: change a title, move a sound cue or replace a screen. Look at what happens to the surrounding sequence. That second edit tells you which parts remain accessible and where another generation or manual adjustment is needed.
In CoAnimator, you can start from a template and direct the connected agent in plain language. Its free forever plan is a starting point for using the studio; agent accounts and optional media services have separate requirements. For a software demonstration, the product demo guide walks through the preparation and production in more detail.
Beginner questions
Do I need to know how to code?
Many AI editors let you work through text, a transcript or visual controls without writing code. An agent-directed studio can also author project code on your behalf. You still need to prepare the source material, connect any required account and judge the result. Access to a coding agent is one setup, not a requirement shared by every AI video editor.
Can an AI video editor work offline?
Some operations can run on your computer, while others call online services. Speech transcription, for example, may use a downloaded local model or a hosted service depending on the application. CoAnimator’s local caption tool transcribes on the machine after its dependencies are prepared, while connected agents and generation services can require the network. Check the specific operation rather than treating “desktop app” as an offline guarantee.
Does using AI mean the entire video is generated?
No. AI can help arrange existing media, animate a title or produce captions for an otherwise unchanged recording. In the Website Demo, existing website captures sit inside an animated device scene. Using AI to build or revise that composition does not mean every image in it was generated.
Start with the change you need
An AI video editor is useful when it turns a clear request into a change you can examine. Begin with the actual job: selecting dialogue, changing shot content, building an explanation or revising an existing project. That choice tells you which capabilities matter.
For your first attempt, keep the source short and the review specific. Listen to the cut, read the title and make one correction. Save the project with the export. Once you understand how that editor handles your media and revisions, you can give it a larger production with much clearer expectations.